TY - JOUR
T1 - A multidimensional index and staging system for idiopathic pulmonary fibrosis
AU - Ley, Brett
AU - Ryerson, Christopher J.
AU - Vittinghoff, Eric
AU - Ryu, Jay H.
AU - Tomassetti, Sara
AU - Lee, Joyce S.
AU - Poletti, Venerino
AU - Buccioli, Matteo
AU - Elicker, Brett M.
AU - Jones, Kirk D.
AU - King, Talmadge E.
AU - Collard, Harold R.
PY - 2012
Y1 - 2012
N2 - Background: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease with an overall poor prognosis. A simple-to-use staging system for IPF may improve prognostication, help guide management, and facilitate research. Objective: To develop a multidimensional prognostic staging system for IPF by using commonly measured clinical and physiologic variables. Design: A clinical prediction model was developed and validated by using retrospective data from 3 large, geographically distinct cohorts. Setting: Interstitial lung disease referral centers in California, Minnesota, and Italy. Patients: 228 patients with IPF at the University of California, San Francisco (derivation cohort), and 330 patients at the Mayo Clinic and Morgagni-Pierantoni Hospital (validation cohort). Measurements: The primary outcome was mortality, treating transplantation as a competing risk. Model discrimination was assessed by the c-index, and calibration was assessed by comparing predicted and observed cumulative mortality at 1, 2, and 3 years. Results: Four variables were included in the final model: gender (G), age (A), and 2 lung physiology variables (P) (FVC and DLCO). A model using continuous predictors (GAP calculator) and a simple point-scoring system (GAP index) performed similarly in derivation (c-index of 70.8 and 69.3, respectively) and validation (c-index of 69.1 and 68.7, respectively). Three stages (stages I, II, and III) were identified based on the GAP index with 1-year mortality of 6%, 16%, and 39%, respectively. The GAP models performed similarly in pooled follow-up visits (c-index ≥71.9). Limitation: Patients were drawn from academic centers and analyzed retrospectively. Conclusion: The GAP models use commonly measured clinical and physiologic variables to predict mortality in patients with IPF. Primary Funding Source: University of California, San Francisco Clinical and Translational Science Institute.
AB - Background: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease with an overall poor prognosis. A simple-to-use staging system for IPF may improve prognostication, help guide management, and facilitate research. Objective: To develop a multidimensional prognostic staging system for IPF by using commonly measured clinical and physiologic variables. Design: A clinical prediction model was developed and validated by using retrospective data from 3 large, geographically distinct cohorts. Setting: Interstitial lung disease referral centers in California, Minnesota, and Italy. Patients: 228 patients with IPF at the University of California, San Francisco (derivation cohort), and 330 patients at the Mayo Clinic and Morgagni-Pierantoni Hospital (validation cohort). Measurements: The primary outcome was mortality, treating transplantation as a competing risk. Model discrimination was assessed by the c-index, and calibration was assessed by comparing predicted and observed cumulative mortality at 1, 2, and 3 years. Results: Four variables were included in the final model: gender (G), age (A), and 2 lung physiology variables (P) (FVC and DLCO). A model using continuous predictors (GAP calculator) and a simple point-scoring system (GAP index) performed similarly in derivation (c-index of 70.8 and 69.3, respectively) and validation (c-index of 69.1 and 68.7, respectively). Three stages (stages I, II, and III) were identified based on the GAP index with 1-year mortality of 6%, 16%, and 39%, respectively. The GAP models performed similarly in pooled follow-up visits (c-index ≥71.9). Limitation: Patients were drawn from academic centers and analyzed retrospectively. Conclusion: The GAP models use commonly measured clinical and physiologic variables to predict mortality in patients with IPF. Primary Funding Source: University of California, San Francisco Clinical and Translational Science Institute.
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U2 - 10.7326/0003-4819-156-10-201205150-00004
DO - 10.7326/0003-4819-156-10-201205150-00004
M3 - Article
C2 - 22586007
AN - SCOPUS:84861162888
SN - 0003-4819
VL - 156
SP - 684
EP - 695
JO - Annals of internal medicine
JF - Annals of internal medicine
IS - 10
ER -